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This paper focuses on the optimal siting of Battery Energy Storage Systems (BESS) in a Distribution Network (DN) with installed Wind Generation (WG), in order to minimize the energy losses and reduce the power load fluctuation of the DN. The bus voltage limit, as well as the ampacity level of the lines are taken into consideration as constraints, while the technical characteristics of BESSs and WG have also been taken into account. In order to propose a solution for this optimization problem, the Unified version of the Particle Swarm Optimization technique is utilized, called UPSO. Simulations have been carried out on the typical 33-Bus system and the results are presented and compared. It is deduced that the introduction of BESSs can aid to the high penetration of WG, blunting the latter's severe consequences on the DN, reducing energy losses, and line ampacity levels and improving the voltage profile of the DN.

This paper examines voltage quality problems in Low Voltage (LV) Distribution Networks (DNs) due to high Photovoltaic (PV) and Electric Vehicles (EVs) penetration. The proposed methodology considers Battery Energy Storage Systems (BESSs) along with the PV units in order to store the energy surplus that causes overvoltage during the high PV generation. This stored energy is utilized at night when the majority of the EVs is expected to be charged. Moreover, a Unified Particle Swarm Optimization (UPSO) algorithm is used in order to optimally schedule EVs charging during the night and under different charging modes. This scheduling is implemented under either an assumed continuous charging mode or an intermittent one. The objective function is set to be the optimal voltage profile. A real LV DN with real measured load data is examined. Variations have been taken into account about some EVs' parameters and the results indicate that the voltage profile is significantly improved under the proposed charging schedule by the UPSO. If this charging schedule is combined with efficient exploitation of the BESS stored energy then the improvement is even higher. The proposed approach also improves energy efficiency towards the implementation of the Nearly Zero Energy Buildings (NZEB) concept.